Mining wikipedia revision histories for improving sentence compression

ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

Volumn , Issue , 2008, Pages 137-151

  Yamangil, Elif ^a   Nelken, Rani ^a  

^a HARVARD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPRESSION RATES; NOISY CHANNEL MODELS; ORDERS OF MAGNITUDE; SENTENCE COMPRESSION; TRAINING CORPUS; TRAINING DATA; WIKIPEDIA;

COMPUTATIONAL LINGUISTICS;

EID: 80053236050     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1557690.1557726     Document Type: Conference Paper

References (8)

1. Michael Collins. 1997. Three generative, lexicalized models for statistical parsing. In Philip R. Cohen and WolfgangWahlster, editors, Proceedings of the Thirty- Fifth Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics, pages 16-23, Somerset, New Jersey. Association for Computational Linguistics.
2. H. Daume, Kevin Knight, I Langkilde-Geary, Daniel Marcu, and K Yamada. 2002. The importance of lexicalized syntax models for natural language generation tasks. Proceedings of the Second International Conference on Natural Language Generation. Arden House, NJ, July 1-3.
3. Kevin Knight and Daniel Marcu. 2000. Statisticsbased summarization - step one: Sentence compression. In Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence, pages 703-710. AAAI Press/The MIT Press.
4. Irene Langkilde. 2000. Forest-based statistical sentence generation. In Proceedings of the first conference on North American chapter of the Association for Computational Linguistics, pages 170-177, San Francisco, CA, USA. Morgan Kaufmann Publishers Inc.
5. Ryan T. McDonald. 2006. Discriminative sentence compression with soft syntactic evidence. In Proceedings of EACL 2006, 11st Conference of the European Chapter of the Association for Computational Linguistics, April 3-7, 2006, Trento, Italy, pages 297-304.
6. Jenine Turner and Eugene Charniak. 2005. Supervised and unsupervised learning for sentence compression. In ACL'05: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pages 290-297, Morristown, NJ, USA. Association for Computational Linguistics.
7. Fernanda B. Víegas, Martin Wattenberg, and Kushal Dave. 2004. Studying cooperation and conflict between authors with istory flow visualizations. In Elizabeth Dykstra-Erickson and Manfred Tscheligi, editors, CHI, pages 575-582. ACM.
8. I.Witten and T. Bell. 1991. The zero-frequency problem: Estimating the probabilities of novel events in adaptive text compression. IEEE Transactions on Information Theory, 37(4).